






'''simple docstring'''




import argparse
import json
import logging
import os
import sys
from unittest.mock import patch

from transformers.testing_utils import TestCasePlus, get_gpu_count, slow


lowerCamelCase_				   =   [
    os.path.join(os.path.dirname(__file__), dirname)
    for dirname in [
        """text-classification""",
        """language-modeling""",
        """summarization""",
        """token-classification""",
        """question-answering""",
    ]
]
sys.path.extend(SRC_DIRS)


if SRC_DIRS is not None:
    import run_clm_flax
    import run_flax_glue
    import run_flax_ner
    import run_mlm_flax
    import run_qa
    import run_summarization_flax
    import run_ta_mlm_flax


logging.basicConfig(level=logging.DEBUG)

lowerCamelCase_				   =   logging.getLogger()

def    __lowercase		(     )			->		Dict:

      '''simple docstring'''


      _A     	=      argparse.ArgumentParser()
      parser.add_argument("-f"			)
      _A     	=      parser.parse_args()
      return args.f

def    __lowercase		(     __lowercase  ,    __lowercase="eval"			)			->		Optional[Any]:

      '''simple docstring'''


      _A     	=      os.path.join(__lowercase  ,    F'''{split}_results.json'''			)
      if os.path.exists(__lowercase			):
            with open(__lowercase  ,    "r"			) as f:
                  return json.load(__lowercase			)
      raise ValueError(F'''can\'t find {path}'''			)


lowerCamelCase_				   =   logging.StreamHandler(sys.stdout)
logger.addHandler(stream_handler)


class   _UpperCAmelCase     (	snake_case_		):




   """simple docstring"""

   def 		lowerCAmelCase					(						self					:      Optional[Any]						):





         '''simple docstring'''





         _A     	=      self.get_auto_remove_tmp_dir()
         _A     	=      f'''\n            run_glue.py\n            --model_name_or_path distilbert-base-uncased\n            --output_dir {tmp_dir}\n            --train_file ./tests/fixtures/tests_samples/MRPC/train.csv\n            --validation_file ./tests/fixtures/tests_samples/MRPC/dev.csv\n            --per_device_train_batch_size=2\n            --per_device_eval_batch_size=1\n            --learning_rate=1e-4\n            --eval_steps=2\n            --warmup_steps=2\n            --seed=42\n            --max_seq_length=128\n            '''.split()

         with patch.object(__UpperCAmelCase , "argv" , __UpperCAmelCase						):
               run_flax_glue.main()
               _A     	=      get_results(__UpperCAmelCase						)
               self.assertGreaterEqual(result["eval_accuracy"] , 0.75						)

   @slow
   def 		lowerCAmelCase					(						self					:      Dict						):





         '''simple docstring'''





         _A     	=      self.get_auto_remove_tmp_dir()
         _A     	=      f'''\n            run_clm_flax.py\n            --model_name_or_path distilgpt2\n            --train_file ./tests/fixtures/sample_text.txt\n            --validation_file ./tests/fixtures/sample_text.txt\n            --do_train\n            --do_eval\n            --block_size 128\n            --per_device_train_batch_size 4\n            --per_device_eval_batch_size 4\n            --num_train_epochs 2\n            --logging_steps 2 --eval_steps 2\n            --output_dir {tmp_dir}\n            --overwrite_output_dir\n            '''.split()

         with patch.object(__UpperCAmelCase , "argv" , __UpperCAmelCase						):
               run_clm_flax.main()
               _A     	=      get_results(__UpperCAmelCase						)
               self.assertLess(result["eval_perplexity"] , 100						)

   @slow
   def 		lowerCAmelCase					(						self					:      Any						):





         '''simple docstring'''





         _A     	=      self.get_auto_remove_tmp_dir()
         _A     	=      f'''\n            run_summarization.py\n            --model_name_or_path t5-small\n            --train_file tests/fixtures/tests_samples/xsum/sample.json\n            --validation_file tests/fixtures/tests_samples/xsum/sample.json\n            --test_file tests/fixtures/tests_samples/xsum/sample.json\n            --output_dir {tmp_dir}\n            --overwrite_output_dir\n            --num_train_epochs=3\n            --warmup_steps=8\n            --do_train\n            --do_eval\n            --do_predict\n            --learning_rate=2e-4\n            --per_device_train_batch_size=2\n            --per_device_eval_batch_size=1\n            --predict_with_generate\n        '''.split()

         with patch.object(__UpperCAmelCase , "argv" , __UpperCAmelCase						):
               run_summarization_flax.main()
               _A     	=      get_results(__UpperCAmelCase , split="test"						)
               self.assertGreaterEqual(result["test_rouge1"] , 10						)
               self.assertGreaterEqual(result["test_rouge2"] , 2						)
               self.assertGreaterEqual(result["test_rougeL"] , 7						)
               self.assertGreaterEqual(result["test_rougeLsum"] , 7						)

   @slow
   def 		lowerCAmelCase					(						self					:      Any						):





         '''simple docstring'''





         _A     	=      self.get_auto_remove_tmp_dir()
         _A     	=      f'''\n            run_mlm.py\n            --model_name_or_path distilroberta-base\n            --train_file ./tests/fixtures/sample_text.txt\n            --validation_file ./tests/fixtures/sample_text.txt\n            --output_dir {tmp_dir}\n            --overwrite_output_dir\n            --max_seq_length 128\n            --per_device_train_batch_size 4\n            --per_device_eval_batch_size 4\n            --logging_steps 2 --eval_steps 2\n            --do_train\n            --do_eval\n            --num_train_epochs=1\n        '''.split()

         with patch.object(__UpperCAmelCase , "argv" , __UpperCAmelCase						):
               run_mlm_flax.main()
               _A     	=      get_results(__UpperCAmelCase						)
               self.assertLess(result["eval_perplexity"] , 42						)

   @slow
   def 		lowerCAmelCase					(						self					:      Union[str, Any]						):





         '''simple docstring'''





         _A     	=      self.get_auto_remove_tmp_dir()
         _A     	=      f'''\n            run_t5_mlm_flax.py\n            --model_name_or_path t5-small\n            --train_file ./tests/fixtures/sample_text.txt\n            --validation_file ./tests/fixtures/sample_text.txt\n            --do_train\n            --do_eval\n            --max_seq_length 128\n            --per_device_train_batch_size 4\n            --per_device_eval_batch_size 4\n            --num_train_epochs 2\n            --logging_steps 2 --eval_steps 2\n            --output_dir {tmp_dir}\n            --overwrite_output_dir\n            '''.split()

         with patch.object(__UpperCAmelCase , "argv" , __UpperCAmelCase						):
               run_ta_mlm_flax.main()
               _A     	=      get_results(__UpperCAmelCase						)
               self.assertGreaterEqual(result["eval_accuracy"] , 0.42						)

   @slow
   def 		lowerCAmelCase					(						self					:      Any						):





         '''simple docstring'''





         _A     	=      7 if get_gpu_count() > 1 else 2

         _A     	=      self.get_auto_remove_tmp_dir()
         _A     	=      f'''\n            run_flax_ner.py\n            --model_name_or_path bert-base-uncased\n            --train_file tests/fixtures/tests_samples/conll/sample.json\n            --validation_file tests/fixtures/tests_samples/conll/sample.json\n            --output_dir {tmp_dir}\n            --overwrite_output_dir\n            --do_train\n            --do_eval\n            --warmup_steps=2\n            --learning_rate=2e-4\n            --logging_steps 2 --eval_steps 2\n            --per_device_train_batch_size=2\n            --per_device_eval_batch_size=2\n            --num_train_epochs={epochs}\n            --seed 7\n        '''.split()

         with patch.object(__UpperCAmelCase , "argv" , __UpperCAmelCase						):
               run_flax_ner.main()
               _A     	=      get_results(__UpperCAmelCase						)
               self.assertGreaterEqual(result["eval_accuracy"] , 0.75						)
               self.assertGreaterEqual(result["eval_f1"] , 0.3						)

   @slow
   def 		lowerCAmelCase					(						self					:      List[Any]						):





         '''simple docstring'''





         _A     	=      self.get_auto_remove_tmp_dir()
         _A     	=      f'''\n            run_qa.py\n            --model_name_or_path bert-base-uncased\n            --version_2_with_negative\n            --train_file tests/fixtures/tests_samples/SQUAD/sample.json\n            --validation_file tests/fixtures/tests_samples/SQUAD/sample.json\n            --output_dir {tmp_dir}\n            --overwrite_output_dir\n            --num_train_epochs=3\n            --warmup_steps=2\n            --do_train\n            --do_eval\n            --logging_steps 2 --eval_steps 2\n            --learning_rate=2e-4\n            --per_device_train_batch_size=2\n            --per_device_eval_batch_size=1\n        '''.split()

         with patch.object(__UpperCAmelCase , "argv" , __UpperCAmelCase						):
               run_qa.main()
               _A     	=      get_results(__UpperCAmelCase						)
               self.assertGreaterEqual(result["eval_f1"] , 30						)
               self.assertGreaterEqual(result["eval_exact"] , 30						)






"""simple docstring"""



from typing import Union

import fire
import torch
from tqdm import tqdm



def 	_lowerCamelCase(	a   ,    a = "cpu"   ,    a = None				):
       __a       =    torch.load(a   ,    map_location=a				)
       for k, v in tqdm(state_dict.items()				):
              if not isinstance(a   ,    torch.Tensor				):
                     raise TypeError("FP16 conversion only works on paths that are saved state dicts, like pytorch_model.bin"				)
              __a       =    v.half()
       if save_path is None:  # overwrite src_path
              __a       =    src_path
       torch.save(a   ,    a				)


if __name__ == "__main__":
   fire.Fire(convert)
